Abstract

Abstract: Identifying competitors is important forbusinesses. In the current competitive business scenario, it is necessary toidentify the competitive characteristics and factors of an article that mostaffect its competitiveness. This study shows the importance of recognizing andobserving contestants of the company. This activity in the framework, manyquestions arise, such as: Who are the key competitors of a particular item?What are the different features of the item that affect its competitiveness?Motivated from this issue, management and advertising groups concentrate onobserving strategies for competitors that distinguish evidence. From thisprevious inspection, concentrate on mining the nearby products, e. g oneproduct is better than the other from other documentary sources. To find thetop competitors the system proposes a KNN algorithm. KNN algorithm can be usedfor classification. Using K- means algorithm unstructured data is structured.After that this structured data is clustered into the appropriate domain. Inpreviously system Apriori algorithm is used for pattern matching, but theproposed system uses the Eclat algorithm for pattern matching. Eclat algorithmidentifies each frequent item. It finds the frequent patterns in dataset, forexample if user buys milk he also buys bread. Finally, the system shows that the proposed system is more accurate thanthe existing system.

Keywords: Competitive business, Competitiveness assessment, KNN algorithm, Apriori algorithm, Eclatalgorithm. Data mining,